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Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays

Nature Genetics volume 36, pages 1331–1339 (2004)Cite this article

Abstract

We developed a new DNA microarray-based technology, called protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the in vitro DNA binding–site sequence specificities of transcription factors in a single day. Using PBMs, we identified the DNA binding–site sequence specificities of the yeast transcription factors Abf1, Rap1 and Mig1. Comparison of these proteins' in vitro binding sites with their in vivo binding sites indicates that PBM-derived sequence specificities can accurately reflect in vivo DNA sequence specificities. In addition to previously identified targets, Abf1, Rap1 and Mig1 bound to 107, 90 and 75 putative new target intergenic regions, respectively, many of which were upstream of previously uncharacterized open reading frames. Comparative sequence analysis indicated that many of these newly identified sites are highly conserved across five sequenced sensu stricto yeast species and, therefore, are probably functional in vivo binding sites that may be used in a condition-specific manner. Similar PBM experiments should be useful in identifying new cis regulatory elements and transcriptional regulatory networks in various genomes.

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Figure 1: PBM schematic.
Figure 2: Identifying the specifically bound spots.
Figure 3: DNA binding site motifs as determined by PBMs compared with motifs derived from ChIP-chip data and from TRANSFAC.
Figure 4: EMSAs of PBM-derived Rap1 binding-site sequences.
Figure 5: Comparison of bound intergenic regions derived from PBM data as compared with those derived from ChIP-chip5,6.
Figure 6: Cross-species sequence conservation of binding sites identified from PBM data as compared with those identified from ChIP-chip data.

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Acknowledgements

We thank T. Volkert and T. Lee for synthesis of the whole-genome yeast intergenic microarrays, B. Huber for assistance with motif searches, L. Campbell and M. Blayney for technical assistance and M. Chou and A. Philippakis for discussion. This work was supported by National Institutes of Health grants from the National Human Genome Research Institute to M.L.B. and to R.Y. and from the National Institute of General Medical Sciences to M.S. M.L.B. was also supported by a Pharmaceutical Research and Manufacturers of America Foundation Informatics Research Starter Grant and an HST Taplin Award. S.M. was supported in part by the MIT Class of 1973 Undergraduate Research Opportunities Program Fund and an MIT Bioengineering Undergraduate Research Award. M.F.B. was supported in part by a Graduate Research Fellowship from the National Science Foundation.

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Author notes

  1. Sonali Mukherjee and Michael F Berger: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Genetics, Department of Medicine, Harvard Medical School,

    Sonali Mukherjee, Michael F Berger, Xun S Wang, Dale Muzzey & Martha L Bulyk

  2. Boston, 02115, Massachusetts, USA

    Sonali Mukherjee, Michael F Berger, Xun S Wang, Dale Muzzey & Martha L Bulyk

  3. Harvard/MIT Division of Health Sciences and Technology, Brigham and Women's Hospital and Harvard Medical School,

    Sonali Mukherjee & Martha L Bulyk

  4. Boston, 02115, Massachusetts, USA

    Sonali Mukherjee & Martha L Bulyk

  5. Harvard University Graduate Biophysics Program, Harvard Medical School,

    Michael F Berger, Dale Muzzey & Martha L Bulyk

  6. Boston, 02115, Massachusetts, USA

    Michael F Berger, Dale Muzzey & Martha L Bulyk

  7. Departments of Molecular, Cellular and Developmental Biology, Yale University, New Haven, 06520, Connecticut, USA

    Ghil Jona & Michael Snyder

  8. Department of Biology, Massachusetts Institute of Technology, Cambridge, 02139, Massachusetts, USA

    Xun S Wang & Richard A Young

  9. Molecular Biophysics and Biochemistry, and Genetics, Yale University, New Haven, 06520, Connecticut, USA

    Michael Snyder

  10. Whitehead Institute for Biomedical Research, Cambridge, 02142, Massachusetts, USA

    Richard A Young

  11. Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, 02115, Massachusetts, USA

    Martha L Bulyk

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Correspondence to Martha L Bulyk.

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Supplementary information

Supplementary Fig. 1

DNA microarray bound by CBP-FLAG-Rpn4. (PDF 103 kb)

Supplementary Fig. 2

Negative control PBMs. (PDF 103 kb)

Supplementary Fig. 3

Reproducibility of PBM data. (PDF 369 kb)

Supplementary Fig. 4

Effect of less stringent P-value thresholds on the number of spots identified as bound. (PDF 23 kb)

Supplementary Fig. 5

Binding site motifs for PBM data passing less stringent P-value thresholds. (PDF 71 kb)

Supplementary Fig. 6

Comparison of bound intergenic regions derived from PBM versus ChIP-chip data at various P-value thresholds. (PDF 279 kb)

Supplementary Methods (HTM 23 kb)

Supplementary Note (PDF 4 kb)

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Mukherjee, S., Berger, M., Jona, G. et al. Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays. Nat Genet 36, 1331–1339 (2004). https://doi.org/10.1038/ng1473

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